{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A simple example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "digits = datasets.load_digits()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optical Recognition of Handwritten Digits Data Set\n",
      "===================================================\n",
      "\n",
      "Notes\n",
      "-----\n",
      "Data Set Characteristics:\n",
      "    :Number of Instances: 5620\n",
      "    :Number of Attributes: 64\n",
      "    :Attribute Information: 8x8 image of integer pixels in the range 0..16.\n",
      "    :Missing Attribute Values: None\n",
      "    :Creator: E. Alpaydin (alpaydin '@' boun.edu.tr)\n",
      "    :Date: July; 1998\n",
      "\n",
      "This is a copy of the test set of the UCI ML hand-written digits datasets\n",
      "http://archive.ics.uci.edu/ml/datasets/Optical+Recognition+of+Handwritten+Digits\n",
      "\n",
      "The data set contains images of hand-written digits: 10 classes where\n",
      "each class refers to a digit.\n",
      "\n",
      "Preprocessing programs made available by NIST were used to extract\n",
      "normalized bitmaps of handwritten digits from a preprinted form. From a\n",
      "total of 43 people, 30 contributed to the training set and different 13\n",
      "to the test set. 32x32 bitmaps are divided into nonoverlapping blocks of\n",
      "4x4 and the number of on pixels are counted in each block. This generates\n",
      "an input matrix of 8x8 where each element is an integer in the range\n",
      "0..16. This reduces dimensionality and gives invariance to small\n",
      "distortions.\n",
      "\n",
      "For info on NIST preprocessing routines, see M. D. Garris, J. L. Blue, G.\n",
      "T. Candela, D. L. Dimmick, J. Geist, P. J. Grother, S. A. Janet, and C.\n",
      "L. Wilson, NIST Form-Based Handprint Recognition System, NISTIR 5469,\n",
      "1994.\n",
      "\n",
      "References\n",
      "----------\n",
      "  - C. Kaynak (1995) Methods of Combining Multiple Classifiers and Their\n",
      "    Applications to Handwritten Digit Recognition, MSc Thesis, Institute of\n",
      "    Graduate Studies in Science and Engineering, Bogazici University.\n",
      "  - E. Alpaydin, C. Kaynak (1998) Cascading Classifiers, Kybernetika.\n",
      "  - Ken Tang and Ponnuthurai N. Suganthan and Xi Yao and A. Kai Qin.\n",
      "    Linear dimensionalityreduction using relevance weighted LDA. School of\n",
      "    Electrical and Electronic Engineering Nanyang Technological University.\n",
      "    2005.\n",
      "  - Claudio Gentile. A New Approximate Maximal Margin Classification\n",
      "    Algorithm. NIPS. 2000.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(digits.DESCR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['DESCR', 'data', 'images', 'target', 'target_names']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(digits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797, 64) (1797,)\n",
      "[0 1 2 3 4 5 6 7 8 9]\n"
     ]
    }
   ],
   "source": [
    "print(digits.data.shape, digits.target.shape) #  data in (nsamples, nfeatures), target in (nsample, )\n",
    "print(digits.target_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estimators objects\n",
    "In scikit-learn, an estimator for classification is a Python object that implements the methods `fit(X, y)` and `predict(T)`.\n",
    "\n",
    "**Fitting data**: the main API implemented by scikit-learn is that of the estimator. An estimator is any object that learns from data; it may be a classification, regression or clustering algorithm or a transformer that extracts/filters useful features from raw data.\n",
    "\n",
    "All estimator objects expose a fit method that takes a dataset:\n",
    "```python\n",
    ">>> estimator.fit(data)\n",
    "```\n",
    "\n",
    "**Estimator parameters**: All the parameters of an estimator can be set when it is instantiated or by modifying the corresponding attribute.\n",
    "```python\n",
    ">>> estimator = Estimator(param1=1, param2=2)\n",
    ">>> estimator.param1\n",
    "1\n",
    "```\n",
    "\n",
    "**Estimated parameters**: When data is fitted with an estimator, parameters are estimated from the data at hand. *All the estimated parameters are attributes of the estimator object ending by an underscore*.\n",
    "```python\n",
    ">>> estimator.estimated_param_\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import svm\n",
    "clf = svm.SVC(gamma=0.001, C=100.) # create a svc estimator object"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Learning and predicting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=100.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "  decision_function_shape='ovr', degree=3, gamma=0.001, kernel='rbf',\n",
       "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "  tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(digits.data[:-1], digits.target[:-1]) # learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predict: [8]\n",
      "Truth: 8\n"
     ]
    }
   ],
   "source": [
    "print('Predict:', clf.predict(digits.data[-1:, :])) # predicting\n",
    "print('Truth:', digits.target[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f2b83d3e278>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2b83dbfa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(digits.data[-1, :].reshape(8, 8), cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model persistence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can save the skikit model using `pickle` or `joblib`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pickle\n",
    "s = pickle.dumps(clf) # dump to a string\n",
    "clf2 = pickle.loads(s) # load from a string\n",
    "clf2.predict(digits.data[-1:, :])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use joblib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`joblib` is more efficient on big data, but can only pickle to the disk and not to a string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.externals import joblib\n",
    "joblib.dump(clf, 'myclf.pkl') # dump to a file\n",
    "clf3 = joblib.load('myclf.pkl') # load from a file\n",
    "clf3.predict(digits.data[-1:, :])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Supervised learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare data sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import model_selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "iris = datasets.load_iris()\n",
    "X_train, X_test, y_train, y_test = model_selection.train_test_split(iris.data, iris.target, test_size=0.2, random_state=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### About Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC\n",
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from sklearn.preprocessing import LabelBinarizer\n",
    "from sklearn.preprocessing import MultiLabelBinarizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 0 0]\n",
      " [1 0 0]\n",
      " [0 1 0]\n",
      " [0 1 0]\n",
      " [0 0 1]]\n"
     ]
    }
   ],
   "source": [
    "y = [0, 0, 1, 1, 2]\n",
    "print(LabelBinarizer().fit_transform(y)) # convert to one-hot vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1 1 0 0 0]\n",
      " [1 0 1 0 0]\n",
      " [0 1 0 1 0]\n",
      " [1 0 1 1 0]\n",
      " [0 0 1 0 1]]\n"
     ]
    }
   ],
   "source": [
    "y = [[0, 1], [0, 2], [1, 3], [0, 2, 3], [2, 4]]\n",
    "print(MultiLabelBinarizer().fit_transform(y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## k-Nearest neighbors\n",
    "The simplest possible classifier is the **nearest neighbor**: given a new observation X_test, find in the training set (i.e. the data used to train the estimator) the observation with the closest feature vector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=1, n_neighbors=5, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "knn = KNeighborsClassifier(n_neighbors=5) # n=5\n",
    "knn.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 0, 1, 0, 1, 2, 1, 0, 1, 1, 2, 1, 0, 0, 2, 1, 0, 0, 0, 2, 2,\n",
       "       2, 0, 1, 0, 1, 1, 1, 2])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 0, 1, 0, 1, 1, 1, 0, 1, 1, 2, 1, 0, 0, 2, 1, 0, 0, 0, 2, 2,\n",
       "       2, 0, 1, 0, 1, 1, 1, 2])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we have seen, every estimator exposes a `score` method that can judge the quality of the fit (or the prediction) on new data. Bigger is better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9666666666666667\n"
     ]
    }
   ],
   "source": [
    "print(knn.score(X_test, y_test)) # mean accuracy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**The curse of dimensionality**: For an estimator to be effective, you need the distance between neighboring points to be less than some value $d$. If the number of features is $p$, you now require $n \\sim 1/d^p$ points. Let’s say that we require 10 points in one dimension: now $10^p$ points are required in $p$ dimensions to pave the $[0, 1]$ space. As p becomes large, the number of training points required for a good estimator grows exponentially."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linear model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**LinearRegression**: target value is expected to be a linear combination of the input variables, i.e.,\n",
    "\n",
    "$$\\hat{y} = X\\omega + \\omega_0 = \\omega_0 + \\omega_1 x_1 + \\omega_2 x_2 + ... + \\omega_p x_p$$\n",
    "\n",
    "- $X$: data, in (nsamples, nfeatures)\n",
    "- $\\hat{y}$: predict value\n",
    "- $\\omega=(\\omega_1, \\omega_2, ..., \\omega_p)$: coefficients, designate as `coef_`\n",
    "- $\\omega_0$: the interception (designate as `intercept_`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import linear_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ordinary Least Squares\n",
    "It minimize the residual sum of squares between the observed responses in the dataset. Mathematically,\n",
    "$$ \\min_{\\omega, \\omega_0} \\left \\| \\hat{y}-y \\right \\|_2^2$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9116620808967584"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(X_train, y_train)\n",
    "regr.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.049174774967471156"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The mean square error\n",
    "np.mean((regr.predict(X_test)-y_test)**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ordinary Least Squares rely on the independence of the model terms. When terms are highly correlated, the least-squares estimate becomes sensitive to random errors in the observed response, producing a large variance. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ridge Regression\n",
    "**Ridge regression** addresses some of the problems of Ordinary Least Squares by imposing a penalty on the size of coefficients. The ridge coefficients minimize a penalized residual sum of squares,\n",
    "$$ \\min_{\\omega, \\omega_0} \\left ( \\| \\hat{y}-y \\|_2^2 + \\alpha \\| \\omega \\|_2^2 \\right)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9100696972662432"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rreg = linear_model.Ridge(alpha = .5)\n",
    "rreg.fit(X_train, y_train)\n",
    "rreg.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`RidgeCV` implements ridge regression with built-in cross-validation of the alpha parameter. it defaults to Generalized Cross-Validation (GCV), an efficient form of leave-one-out cross-validation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9088449344290264"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rreg2 = linear_model.RidgeCV(alphas=[0.001, 0.1, 1.0, 10.0])\n",
    "rreg2.fit(X_train, y_train)\n",
    "rreg2.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rreg2.alpha_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lasso\n",
    "The **Lasso** (least absolute shrinkage and selection operator) is a linear model that estimates sparse coefficients. It is useful in some contexts due to its tendency to prefer solutions with fewer parameter values, effectively reducing the number of variables upon which the given solution is dependent.\n",
    "The objective function to minimize is:\n",
    "$$ \\min_{\\omega, \\omega_0} \\left ( \\frac{1}{2n_{\\rm samples}} \\| \\hat{y}-y \\|_2^2 + \\alpha \\| \\omega \\|_1^2 \\right)$$\n",
    "\n",
    "Compared with the ridge regression, which will decrease their contribution but not set them to zero, Lasso can set some coefficients to zero. Such methods are called **sparse method**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8772334730650394"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "las = linear_model.Lasso(alpha = 0.1)\n",
    "las.fit(X_train, y_train)\n",
    "las.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.15466448 -0.01394046  0.30927195  0.47219109]\n",
      "[ 0.         -0.          0.41327267  0.        ]\n"
     ]
    }
   ],
   "source": [
    "print(rreg.coef_)\n",
    "print(las.coef_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logistic Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Linear regression is not the right approach as it will give too much weight to data far from the decision frontier. A linear approach is to fit a sigmoid function or logistic function:\n",
    "$$\\hat{y} = {\\rm sigmoid}(X\\omega + \\omega_0) = \\frac{1}{1+\\exp(-X\\omega - \\omega_0)}.$$\n",
    "\n",
    "Minimize the cost function (L2 normalization): $\\min_{\\omega, \\omega_0} C(\\omega, \\omega_0),$ where the cost function is\n",
    "\\begin{aligned}\n",
    "C(\\omega, \\omega_0) &= \\frac{1}{2}\\omega^T\\omega + C \\sum_i \\left[ y_i \\log(\\hat{y}_i) + (1-y_i)\\log(1-\\hat{y}_i)) \\right] \\\\\n",
    "                    &= \\frac{1}{2}\\omega^T\\omega + C \\sum_i \\log (\\exp(-y_i (X_i^T\\omega+\\omega_0)) + 1),\\ {\\rm for\\ }(y=\\pm 1).\n",
    "\\end{aligned}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "logistic = linear_model.LogisticRegression(C=1e5) # L2 penalty in default\n",
    "logistic.fit(X_train, y_train)\n",
    "logistic.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predict: [0 0 1 0 1]\n",
      "Truth: [0 0 1 0 1]\n"
     ]
    }
   ],
   "source": [
    "print('Predict:', logistic.predict(X_train[10:15])) # predicting\n",
    "print('Truth:', y_train[10:15])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### One-Vs-The-Rest\n",
    "The solver “liblinear” uses a coordinate descent (CD) algorithm, which cannot learn a true multinomial (multiclass) model; instead, the optimization problem is decomposed in a “one-vs-rest” fashion so separate binary classifiers are trained for all classes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "logistic2 = OneVsRestClassifier(estimator=linear_model.LogisticRegression(C=1e5))\n",
    "logistic2.fit(X_train, y_train)\n",
    "logistic2.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Support vector machines"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Support Vector Machines** (SVMs) belong to the discriminant model family: they try to find a combination of samples to build a plane maximizing the margin between the two classes.   \n",
    "SVMs can be used in regression: **SVR** (Support Vector Regression), or in classification: **SVC** (Support Vector Classification)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import svm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Linear kernel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9666666666666667"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svc = svm.SVC(kernel='linear')\n",
    "svc.fit(X_train, y_train)\n",
    "svc.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using kernels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Classes are not always linearly separable in feature space. The solution is to build a decision function that is not linear but may be polynomial instead. This is done using the kernel trick that can be seen as creating a decision energy by positioning kernels on observations:\n",
    "\n",
    "- Linear kernel:\n",
    "    ```python\n",
    "    >>> svc = svm.SVC(kernel='linear')\n",
    "    ```\n",
    "    ![](http://scikit-learn.org/stable/_images/sphx_glr_plot_svm_kernels_001.png)\n",
    "    \n",
    "- Polynomial kernel:\n",
    "    ```python\n",
    "    >>> svc = svm.SVC(kernel='poly', degree=3) # degree: polynomial degree\n",
    "    ```\n",
    "    ![](http://scikit-learn.org/stable/_images/sphx_glr_plot_svm_kernels_002.png)\n",
    "    \n",
    "- RBF kernel (Radial Basis Function):\n",
    "    ```python\n",
    "    >>> svc = svm.SVC(kernel='rbf', gamma=2) # gamma: inverse of size of radial kernel\n",
    "    ```\n",
    "    ![](http://scikit-learn.org/stable/_images/sphx_glr_plot_svm_kernels_003.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Score, and cross-validated scores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get a better measure of prediction accuracy (which we can use as a proxy for goodness of fit of the model), we can successively split the data in folds that we use for training and testing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(0)\n",
    "indices = np.random.permutation(len(iris.data))\n",
    "iris_data_shuffled = iris.data[indices]\n",
    "iris_target_shuffled = iris.target[indices]\n",
    "\n",
    "X_folds = np.array_split(iris_data_shuffled, 3) # randomize the trained set\n",
    "y_folds = np.array_split(iris_target_shuffled, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "svc2 = svm.SVC(C=1, kernel='linear')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### K Folds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.98, 0.98, 0.98]\n"
     ]
    }
   ],
   "source": [
    "# Kfolder cross-validation algorithm\n",
    "scores = list()\n",
    "for k in range(3):\n",
    "    X_train_ = list(X_folds) # copy a X_folds\n",
    "    X_test_  = X_train_.pop(k)\n",
    "    X_train_ = np.concatenate(X_train_)\n",
    "    y_train_ = list(y_folds) # copy a y_folds\n",
    "    y_test_  = y_train_.pop(k)\n",
    "    y_train_ = np.concatenate(y_train_)\n",
    "    scores.append(svc2.fit(X_train_, y_train_).score(X_test_, y_test_))\n",
    "print(scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### use cross-validation generators\n",
    "Scikit-learn has a collection of classes which can be used to generate lists of train/test indices for popular cross-validation strategies. They expose a `split` method which accepts the input dataset to be split and yields the train/test set indices for each iteration of the chosen cross-validation strategy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.98, 0.98, 0.98])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use KFold to manually split samples\n",
    "k_fold = model_selection.KFold(n_splits=3)\n",
    "# use cross_val_score to directly calculate the cross-validation score.\n",
    "# By default the estimator’s score method is used to compute the individual scores.\n",
    "model_selection.cross_val_score(svc2, iris_data_shuffled, iris_target_shuffled, cv=k_fold)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grid-search\n",
    "scikit-learn provides an object that, given data, computes the score during the fit of an estimator on a parameter grid and chooses the parameters to maximize the cross-validation score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=None, error_score='raise',\n",
       "       estimator=SVC(C=1, cache_size=200, class_weight=None, coef0=0.0,\n",
       "  decision_function_shape='ovr', degree=3, gamma='auto', kernel='linear',\n",
       "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "  tol=0.001, verbose=False),\n",
       "       fit_params=None, iid=True, n_jobs=-1,\n",
       "       param_grid={'C': array([1.00000e-06, 5.99484e-06, 3.59381e-05, 2.15443e-04, 1.29155e-03,\n",
       "       7.74264e-03, 4.64159e-02, 2.78256e-01, 1.66810e+00, 1.00000e+01])},\n",
       "       pre_dispatch='2*n_jobs', refit=True, return_train_score='warn',\n",
       "       scoring=None, verbose=0)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV, cross_val_score\n",
    "Cs = np.logspace(-6, 1, 10)\n",
    "clf = GridSearchCV(estimator=svc2, param_grid=dict(C=Cs),\n",
    "                   n_jobs=-1)\n",
    "clf.fit(iris_data_shuffled, iris_target_shuffled) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9733333333333334\n",
      "1.6681005372000592\n"
     ]
    }
   ],
   "source": [
    "print(clf.best_score_)                              \n",
    "print(clf.best_estimator_.C)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unsupervised learning: seeking representations of the data\n",
    "## Clustering: grouping observations together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import cluster"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### K-means clustering\n",
    "The simplest clustering algorithm is K-means."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
       "    n_clusters=3, n_init=10, n_jobs=1, precompute_distances='auto',\n",
       "    random_state=None, tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k_means = cluster.KMeans(n_clusters=3)\n",
    "k_means.fit(iris.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 1 1 1 1 2 2 2 2 2 0 0 0 0 0]\n",
      "[0 0 0 0 0 1 1 1 1 1 2 2 2 2 2]\n"
     ]
    }
   ],
   "source": [
    "print(k_means.labels_[::10])\n",
    "print(iris.target[::10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2b780e0c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 5))\n",
    "for i, title, target in [(1, 'True Labels', iris.target), (2, 'K-means Labels', k_means.labels_)]:\n",
    "    ax = fig.add_subplot(1, 2, i, projection='3d')\n",
    "    ax.scatter(iris.data[:, 3], iris.data[:, 0], iris.data[:, 2], c=target)\n",
    "    ax.set_xlabel('Petal width')\n",
    "    ax.set_ylabel('Sepal length')\n",
    "    ax.set_zlabel('Petal length')\n",
    "    ax.view_init(50., 130.)\n",
    "    ax.set_title(title)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Use K-means to compress the information\n",
    "Clustering in general and KMeans, in particular, can be seen as a way of choosing a small number of exemplars to compress the information. The problem is sometimes known as **vector quantization**. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import misc\n",
    "face = misc.face(gray=True)\n",
    "k_means = cluster.KMeans(n_clusters=5, n_init=1)\n",
    "k_means.fit(face.reshape(-1, 1))\n",
    "face_compress = np.choose(k_means.labels_, k_means.cluster_centers_.squeeze()).reshape(face.shape) # choose the center value of the cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'compressed image')"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2b7802ddd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 5))\n",
    "ax1 = fig.add_subplot(121)\n",
    "ax1.imshow(face, cmap='gray', vmin=0, vmax=256)\n",
    "ax1.set_title('raw image')\n",
    "\n",
    "ax2 = fig.add_subplot(122)\n",
    "ax2.imshow(face_compress, cmap='gray', vmin=0, vmax=256)\n",
    "ax2.set_title('compressed image')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature agglomeration\n",
    "Another approach is to merge together similar features: feature agglomeration. This approach can be implemented by clustering in the feature direction, in other words clustering the transposed data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.image import grid_to_graph\n",
    "\n",
    "X = np.reshape(digits.images, (len(digits.images), -1))\n",
    "\n",
    "connectivity = grid_to_graph(*digits.images[0].shape) # graph of pixel to pixel connections\n",
    "agglo = cluster.FeatureAgglomeration(connectivity=connectivity, n_clusters=32)\n",
    "agglo.fit(X) \n",
    "\n",
    "X_reduced = agglo.transform(X)\n",
    "X_approx = agglo.inverse_transform(X_reduced)\n",
    "images_approx = np.reshape(X_approx, digits.images.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'agglomerated image')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2b63a44ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 5))\n",
    "ax1 = fig.add_subplot(121)\n",
    "ax1.imshow(digits.images[0], cmap='gray')\n",
    "ax1.set_title('original image')\n",
    "\n",
    "ax2 = fig.add_subplot(122)\n",
    "ax2.imshow(images_approx[0].reshape(digits.images[0].shape), cmap='gray')\n",
    "ax2.set_title('agglomerated image')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Decompositions: from a signal to components and loadings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import decomposition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Principal component analysis\n",
    "**Principal component analysis** (PCA) selects the successive components that explain the maximum variance in the signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.random.normal(scale=0.5, size=(100,))\n",
    "y = np.random.normal(scale=0.5, size=len(x))\n",
    "z = np.random.normal(scale=0.1, size=len(x))\n",
    "\n",
    "a = x + y\n",
    "b = 2 * y\n",
    "c = a - b + z\n",
    "\n",
    "X = np.c_[a, b, c]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.92624119 0.48658509 0.00368378]\n"
     ]
    }
   ],
   "source": [
    "pca = decomposition.PCA()\n",
    "pca.fit(X)\n",
    "\n",
    "print(pca.explained_variance_)  \n",
    "\n",
    "pca.n_components = 2 # only the 2 first components are useful\n",
    "X_reduced = pca.fit_transform(X)\n",
    "X_approx = pca.inverse_transform(X_reduced)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pipelining"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = decomposition.PCA()\n",
    "logistic = linear_model.LogisticRegression()\n",
    "pipe = Pipeline(steps=[('pca', pca), ('logistic', logistic)]) # first run pca and then logistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=None, error_score='raise',\n",
       "       estimator=Pipeline(memory=None,\n",
       "     steps=[('pca', PCA(copy=True, iterated_power='auto', n_components=None, random_state=None,\n",
       "  svd_solver='auto', tol=0.0, whiten=False)), ('logistic', LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
       "          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
       "          verbose=0, warm_start=False))]),\n",
       "       fit_params=None, iid=True, n_jobs=1,\n",
       "       param_grid={'pca__n_components': [20, 40, 64], 'logistic__C': array([1.e-04, 1.e+00, 1.e+04])},\n",
       "       pre_dispatch='2*n_jobs', refit=True, return_train_score='warn',\n",
       "       scoring=None, verbose=0)"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grid search parameters\n",
    "n_components = [20, 40, 64]\n",
    "Cs = np.logspace(-4, 4, 3)\n",
    "\n",
    "# grid search\n",
    "estimator = GridSearchCV(pipe, dict(pca__n_components=n_components, logistic__C=Cs))\n",
    "estimator.fit(digits.data, digits.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'logistic__C': 1.0, 'pca__n_components': 40}"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "estimator.best_params_"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
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